3 papers
cs.CL2026
GroundAct: Can LLM Agents Ground Actions in Environmental States?
Zixuan Wang, Dingming Li, Hongxing Li +8
LLM agents achieve 85-96% success on tasks where instructions fully specify the action, but drop to 29-53% when action feasibility depends on environmental state that the instructi…
cs.LG2025
RepDL: Bit-level Reproducible Deep Learning Training and Inference
Peichen Xie, Xian Zhang, Shuo Chen
Non-determinism and non-reproducibility present significant challenges in deep learning, leading to inconsistent results across runs and platforms. These issues stem from two origi…
cs.LG2025
Global Convergence Analysis of Vanilla Gradient Descent for Asymmetric Matrix Completion
Xu Zhang, Shuo Chen, Jinsheng Li +2
This paper investigates the asymmetric low-rank matrix completion problem, which can be formulated as an unconstrained non-convex optimization problem with a nonlinear least-square…